Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory44.2 B

Variable types

Categorical3
Numeric2

Dataset

Description2022년 통신서비스 품질평가 결과 보고서 내 , 전국 85개시 430개 지역 대상의 세부유형별 5G전송속도(Mbps) 결과 데이터
URLhttps://www.data.go.kr/data/15105757/fileData.do

Alerts

다운로드(Mbps) is highly overall correlated with 업로드(Mbps)High correlation
업로드(Mbps) is highly overall correlated with 다운로드(Mbps)High correlation
구분 is highly overall correlated with 상세구분High correlation
상세구분 is highly overall correlated with 구분High correlation
다운로드(Mbps) has unique valuesUnique
업로드(Mbps) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:53:05.606495
Analysis finished2023-12-12 14:53:06.389564
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
다중이용시설
39 
교통인프라
18 
주거지역
 
3

Length

Max length6
Median length6
Mean length5.6
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다중이용시설
2nd row다중이용시설
3rd row다중이용시설
4th row다중이용시설
5th row다중이용시설

Common Values

ValueCountFrequency (%)
다중이용시설 39
65.0%
교통인프라 18
30.0%
주거지역 3
 
5.0%

Length

2023-12-12T23:53:06.471448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:53:06.667850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다중이용시설 39
65.0%
교통인프라 18
30.0%
주거지역 3
 
5.0%

상세구분
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
놀이공원
 
3
주요거리
 
3
여객터미널
 
3
대형점포
 
3
백화점
 
3
Other values (15)
45 

Length

Max length8
Median length6
Mean length4.35
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row놀이공원
2nd row놀이공원
3rd row놀이공원
4th row주요거리
5th row주요거리

Common Values

ValueCountFrequency (%)
놀이공원 3
 
5.0%
주요거리 3
 
5.0%
여객터미널 3
 
5.0%
대형점포 3
 
5.0%
백화점 3
 
5.0%
영화관 3
 
5.0%
지하상가 3
 
5.0%
전통시장 3
 
5.0%
대형병원 3
 
5.0%
전시박물관· 3
 
5.0%
Other values (10) 30
50.0%

Length

2023-12-12T23:53:06.787986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
놀이공원 3
 
5.0%
주요거리 3
 
5.0%
고속도로 3
 
5.0%
철도역사 3
 
5.0%
srt 3
 
5.0%
ktx 3
 
5.0%
지하철역사 3
 
5.0%
지하철객차 3
 
5.0%
도서관 3
 
5.0%
대학교(인빌딩 3
 
5.0%
Other values (10) 30
50.0%

통신사
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
SKT
20 
KT
20 
LGU+
20 

Length

Max length4
Median length3
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSKT
2nd rowKT
3rd rowLGU+
4th rowSKT
5th rowKT

Common Values

ValueCountFrequency (%)
SKT 20
33.3%
KT 20
33.3%
LGU+ 20
33.3%

Length

2023-12-12T23:53:07.221159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:53:07.327187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
skt 20
33.3%
kt 20
33.3%
lgu 20
33.3%

다운로드(Mbps)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean883.83933
Minimum345.83
Maximum1292.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T23:53:07.458518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum345.83
5-th percentile393.8075
Q1768.835
median911.375
Q31045.3075
95-th percentile1190.7005
Maximum1292.35
Range946.52
Interquartile range (IQR)276.4725

Descriptive statistics

Standard deviation219.98551
Coefficient of variation (CV)0.24889763
Kurtosis0.32088539
Mean883.83933
Median Absolute Deviation (MAD)139.9
Skewness-0.67376646
Sum53030.36
Variance48393.626
MonotonicityNot monotonic
2023-12-12T23:53:07.656004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1292.35 1
 
1.7%
996.82 1
 
1.7%
962.6 1
 
1.7%
911.9 1
 
1.7%
921.08 1
 
1.7%
1014.62 1
 
1.7%
1036.24 1
 
1.7%
910.85 1
 
1.7%
920.47 1
 
1.7%
873.57 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
345.83 1
1.7%
372.59 1
1.7%
375.52 1
1.7%
394.77 1
1.7%
478.31 1
1.7%
553.5 1
1.7%
565.42 1
1.7%
605.18 1
1.7%
696.56 1
1.7%
712.92 1
1.7%
ValueCountFrequency (%)
1292.35 1
1.7%
1271.11 1
1.7%
1223.2 1
1.7%
1188.99 1
1.7%
1170.44 1
1.7%
1121.99 1
1.7%
1117.94 1
1.7%
1098.5 1
1.7%
1093.63 1
1.7%
1085.73 1
1.7%

업로드(Mbps)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.464
Minimum42.35
Maximum137.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T23:53:07.837388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.35
5-th percentile49.149
Q178.695
median92.375
Q3105.8175
95-th percentile128.012
Maximum137.01
Range94.66
Interquartile range (IQR)27.1225

Descriptive statistics

Standard deviation21.553938
Coefficient of variation (CV)0.23565488
Kurtosis0.086656908
Mean91.464
Median Absolute Deviation (MAD)13.855
Skewness-0.31195096
Sum5487.84
Variance464.57224
MonotonicityNot monotonic
2023-12-12T23:53:08.041524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.99 1
 
1.7%
91.83 1
 
1.7%
96.1 1
 
1.7%
87.12 1
 
1.7%
105.55 1
 
1.7%
99.22 1
 
1.7%
86.91 1
 
1.7%
99.07 1
 
1.7%
101.04 1
 
1.7%
91.1 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
42.35 1
1.7%
44.62 1
1.7%
48.37 1
1.7%
49.19 1
1.7%
49.54 1
1.7%
52.46 1
1.7%
69.6 1
1.7%
72.1 1
1.7%
72.31 1
1.7%
73.66 1
1.7%
ValueCountFrequency (%)
137.01 1
1.7%
134.49 1
1.7%
128.43 1
1.7%
127.99 1
1.7%
118.37 1
1.7%
114.05 1
1.7%
113.69 1
1.7%
113.56 1
1.7%
112.98 1
1.7%
112.38 1
1.7%

Interactions

2023-12-12T23:53:06.031271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:53:05.866088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:53:06.116924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:53:05.948102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:53:08.204806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상세구분통신사다운로드(Mbps)업로드(Mbps)
구분1.0001.0000.0000.3550.330
상세구분1.0001.0000.0000.6750.731
통신사0.0000.0001.0000.5770.514
다운로드(Mbps)0.3550.6750.5771.0000.945
업로드(Mbps)0.3300.7310.5140.9451.000
2023-12-12T23:53:08.352475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세구분통신사구분
상세구분1.0000.0000.838
통신사0.0001.0000.000
구분0.8380.0001.000
2023-12-12T23:53:08.473380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
다운로드(Mbps)업로드(Mbps)구분상세구분통신사
다운로드(Mbps)1.0000.8900.2420.2500.390
업로드(Mbps)0.8901.0000.1890.2780.334
구분0.2420.1891.0000.8380.000
상세구분0.2500.2780.8381.0000.000
통신사0.3900.3340.0000.0001.000

Missing values

2023-12-12T23:53:06.233575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:53:06.346709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구분상세구분통신사다운로드(Mbps)업로드(Mbps)
0다중이용시설놀이공원SKT1292.35127.99
1다중이용시설놀이공원KT1170.44108.56
2다중이용시설놀이공원LGU+960.69100.48
3다중이용시설주요거리SKT1081.48137.01
4다중이용시설주요거리KT1051.12112.38
5다중이용시설주요거리LGU+754.0791.29
6다중이용시설여객터미널SKT1223.2118.37
7다중이용시설여객터미널KT1098.5111.47
8다중이용시설여객터미널LGU+925.57102.12
9다중이용시설대형점포SKT1066.6395.95
구분상세구분통신사다운로드(Mbps)업로드(Mbps)
50교통인프라SRTLGU+394.7749.54
51교통인프라철도역사SKT1271.11134.49
52교통인프라철도역사KT1121.99114.05
53교통인프라철도역사LGU+928.0111.14
54교통인프라고속도로SKT715.2480.52
55교통인프라고속도로KT605.1872.1
56교통인프라고속도로LGU+553.573.66
57주거지역아파트SKT992.18104.23
58주거지역아파트KT909.6184.7
59주거지역아파트LGU+769.5876.84